Shahar Mendelson | DeepAI

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Featured Co-authors

Gábor Lugosi
31 publications
Felix Krahmer
29 publications
Afonso S. Bandeira
27 publications
Nikita Zhivotovskiy
25 publications
Holger Rauhut
21 publications
Sjoerd Dirksen
14 publications
Antoine Maillard
14 publications
Elliot Paquette
11 publications
Christian Kümmerle
10 publications
Alexander Stollenwerk
7 publications
Daniel Bartl
5 publications

∙ 08/09/2023

On a variance dependent Dvoretzky-Kiefer-Wolfowitz inequality

Let X be a real-valued random variable with distribution function F. Set...

0 Daniel Bartl, et al. ∙

∙ 07/03/2023

Fitting an ellipsoid to a quadratic number of random points

We consider the problem (P) of fitting n standard Gaussian random vector...

0 Afonso S. Bandeira, et al. ∙

∙ 09/15/2022

Structure preservation via the Wasserstein distance

We show that under minimal assumptions on a random vector X∈ℝ^d, and wit...

0 Daniel Bartl, et al. ∙

∙ 04/08/2022

Fast metric embedding into the Hamming cube

We consider the problem of embedding a subset of ℝ^n into a low-dimensio...

0 Sjoerd Dirksen, et al. ∙

∙ 01/13/2022

Sharp estimates on random hyperplane tessellations

We study the problem of generating a hyperplane tessellation of an arbit...

0 Sjoerd Dirksen, et al. ∙

∙ 03/09/2021

Column randomization and almost-isometric embeddings

The matrix A:ℝ^n →ℝ^m is (δ,k)-regular if for any k-sparse vector x, ...

0 Shahar Mendelson, et al. ∙

∙ 01/19/2021

On Monte-Carlo methods in convex stochastic optimization

We develop a novel procedure for estimating the optimizer of general con...

0 Daniel Bartl, et al. ∙

∙ 10/22/2020

Multivariate mean estimation with direction-dependent accuracy

We consider the problem of estimating the mean of a random vector based ...

0 Gábor Lugosi, et al. ∙

∙ 02/04/2020

Learning bounded subsets of L_p

We study learning problems in which the underlying class is a bounded su...

0 Shahar Mendelson, et al. ∙

∙ 07/26/2019

Robust multivariate mean estimation: the optimality of trimmed mean

We consider the problem of estimating the mean of a random vector based ...

0 Gábor Lugosi, et al. ∙

∙ 07/16/2019

On the geometry of polytopes generated by heavy-tailed random vectors

We study the geometry of centrally-symmetric random polytopes, generated...

0 Olivier Guédon, et al. ∙

∙ 06/10/2019

Mean estimation and regression under heavy-tailed distributions--a survey

We survey some of the recent advances in mean estimation and regression ...

0 Gábor Lugosi, et al. ∙

∙ 04/17/2019

Stable recovery and the coordinate small-ball behaviour of random vectors

Recovery procedures in various application in Data Science are based on ...

0 Shahar Mendelson, et al. ∙

∙ 12/17/2018

Robust one-bit compressed sensing with partial circulant matrices

We present optimal sample complexity estimates for one-bit compressed se...

0 Sjoerd Dirksen, et al. ∙

∙ 09/27/2018

Robust covariance estimation under L_4-L_2 norm equivalence

Let X be a centered random vector taking values in R^d and let Σ= E(X⊗ X...

0 Shahar Mendelson, et al. ∙

∙ 06/16/2018

Near-optimal mean estimators with respect to general norms

We study the problem of estimating the mean of a random vector in R^d ba...

0 Gábor Lugosi, et al. ∙

∙ 05/23/2018

Robust one-bit compressed sensing with non-Gaussian measurements

We study memoryless one-bit compressed sensing with non-Gaussian measure...

0 Sjoerd Dirksen, et al. ∙

∙ 04/15/2018

Approximating the covariance ellipsoid

We explore ways in which the covariance ellipsoid B={v ∈R^d : E <X,v>^2...

0 Shahar Mendelson, et al. ∙

∙ 12/19/2017

A remark on "Robust machine learning by median-of-means"

We explore the recent results announced in "Robust machine learning by m...

0 Gábor Lugosi, et al. ∙

∙ 09/04/2017

Extending the small-ball method

The small-ball method was introduced as a way of obtaining a high probab...

0 Shahar Mendelson, et al. ∙

∙ 07/17/2017

An optimal unrestricted learning procedure

We study learning problems in the general setup, for arbitrary classes o...

0 Shahar Mendelson, et al. ∙

∙ 02/21/2017

Column normalization of a random measurement matrix

In this note we answer a question of G. Lecué, by showing that column no...

0 Shahar Mendelson, et al. ∙

∙ 02/01/2017

Sub-Gaussian estimators of the mean of a random vector

We study the problem of estimating the mean of a random vector X given a...

0 Gábor Lugosi, et al. ∙

∙ 01/15/2017

Regularization, sparse recovery, and median-of-means tournaments

A regularized risk minimization procedure for regression function estima...

0 Gábor Lugosi, et al. ∙

∙ 04/09/2015

`local' vs. `global' parameters -- breaking the gaussian complexity barrier

We show that if F is a convex class of functions that is L-subgaussian, ...

0 Shahar Mendelson, et al. ∙

∙ 02/25/2015

On aggregation for heavy-tailed classes

We introduce an alternative to the notion of `fast rate' in Learning The...

0 Shahar Mendelson, et al. ∙

∙ 10/13/2014

Learning without Concentration for General Loss Functions

We study prediction and estimation problems using empirical risk minimiz...

0 Shahar Mendelson, et al. ∙

∙ 01/01/2014

Learning without Concentration

We obtain sharp bounds on the performance of Empirical Risk Minimization...

0 Shahar Mendelson, et al. ∙

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